The Consumer Electronics Show (CES) — an annual gathering that showcases next-generation technology innovations — took place in Las Vegas this week. Former Apple CEO John Sculley, who has attended the event since it first launched, notes that unlike the days when visitors saw “display after display of consumer electronics and flat-screen TVs,” the show is now “moving much more towards the capabilities of machine learning, virtual reality, augmented reality — many of these things that are really software based and not hardware based.”

In an interview with the Knowledge@Wharton show on SiriusXM channel 111, Sculley, who is also former CEO of Pepsi and co-founder of marketing technology company Zeta Global, talked about how CES has transformed and how he sees artificial intelligence (AI) taking hold across sectors. “AI is going to be foundational in every industry. I’m seeing it in fintech, market tech, health tech…. It’s one of those fundamental changes. In the previous industrial age, it was all about electricity and oil; in the future [AI is] going to be a commodity that will be deployed in many, many different ways, and will be something you can just plug into.”

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Anumakonda Jagadeesh

Excellent.
AI has become “ALL IN” and pervading at a rapid speed.
Technology moves at breakneck speed, and we now have more power in our pockets than we had in our homes in the 1990s. Artificial intelligence (AI) has been a fascinating concept of science fiction for decades, but many researchers think we’re finally getting close to making AI a reality. NPR notes that in the last few years, scientists have made breakthroughs in “machine learning,” using neural networks, which mimic the processes of real neurons.
Artificial intelligence, defined as intelligence exhibited by machines, has many applications in today’s society. More specifically,the form of A.I. where programs are developed to perform specific tasks, that is being utilized for a wide range of activities including medical diagnosis, electronic trading, robot control, and remote sensing. AI has been used to develop and advance numerous fields and industries, including finance, healthcare, education, transportation, and more.
Computer science
Education
Finance
Algorithmic trading[
Market analysis and data mining
Personal finance
Portfolio management
Underwriting
Heavy industry[
Hospitals and medicine

X-ray of a hand, with automatic calculation of bone age by a computer software.
Main article: Artificial intelligence in healthcare
Artificial neural networks are used as clinical decision support systems for medical diagnosis, such as in Concept Processing technology in EMR software.
Other tasks in medicine that can potentially be performed by artificial intelligence and are beginning to be developed include:
• Computer-aided interpretation of medical images. Such systems help scan digital images, e.g. from computed tomography, for typical appearances and to highlight conspicuous sections, such as possible diseases. A typical application is the detection of a tumor.
• Heart sound analysis
• Watson project is another use of AI in this field, a Q/A program that suggest for doctor’s of cancer patients.
• Companion robots for the care of the elderly
• Mining medical records to provide more useful information.
• Design treatment plans.
• Assist in repetitive jobs including medication management.
• Provide consultations.
• Drug creation
• Using avatars in place of patients for clinical training
Currently, there are over 90 AI startups in the health industry working in these fields.
Human resources and recruiting
Marketing

Music
News, publishing and writing
Online and telephone customer service
Telecommunications maintenance
Toys and games
Transportation
Other
Various tools of artificial intelligence are also being widely deployed in homeland security, speech and text recognition, data mining, and e-mail spam filtering. Applications are also being developed for gesture recognition (understanding of sign language by machines), individual voice recognition, global voice recognition (from a variety of people in a noisy room), facial expression recognition for interpretation of emotion and non verbal cues. Other applications are robot navigation, obstacle avoidance, and object recognition(Wikipedia).